Hello Thankyou for the detailed explaination - I have one question If I have a Wi-Fi setup which provides me the following information at the receiver side - RSSI (signal strength at the receiver) and the Noise floor in dB and the channel frequency response is there any way i can evaluate the capacity of the channel with the above values as I have no acess to baseband signal to get the energy of each bits.?
The easiest thing would be to compute the SNR as the RSSI divided by the Noise power (be careful with the dB-scales). You can then estimate the capacity as "Bandwidth*log2(1+SNR)".
@@WirelessFuture Thankyou for the explaination , just a follow up question : Considering a 2x2 MIMO channel , I have the channel state information of received signal and RSSI and Noise Floor values of each Tx-Rx path, which formulae can I used to estimate the capacity of Wi-fi system ? considering rest other OFDM parameters (MCS, Bandwidth...etc ) is known to me. It would be reallly help- ful for my Thesis work. Thankyou in advance :)
Dear Mr. Bjornson, You have an incredible way to convey your knowledge :) Could you plz make for us a video to explain why the data rate is related to the frequency bandwidth using Fourier transform ? Thx a lot
You don’t need to involve the Fourier transform. Just apply the sampling theorem, which says that a signal is described by a number of samples proportional to the bandwidth. These samples are used to carry information, for example, by designing the signals using pulse-amplitude modulation. It is briefly mentioned in Video 3 and around slide 22 in ruclips.net/video/SR10FeiuAFs/видео.html
Yes, but then the time-domain signal will be complex valued, so such a signal doesn’t exist in practice. However, the non-symmetric complex baseband signal exist and is usually represented as two different signals. (The “in-phase” and “quadrature” signals)
♥️😍 another piece of cake but the equation @3:07 should not be in (Symbol/second) instead (bits/s) because i think it's going to be bits/s after modulating the symbols isn't it ?
If you pause the video at 2:34, you will see expressions in symbol/s and in bit/symbol. If we multiply them together it becomes bit/s. This what is presented at 3:07.
The Shannon limit says there is an upper bound for a reliable communication. Then what is the meaning of "reliable communication"? In other words, if one exceeds the limit, how much deterioration will be brought about?
Suppose we transmit a block of N modulation symbols (samples). If their information content is below the Shannon limit, there is a way to encode the information (select the symbols) so that the probability of incorrect reception of the block goes to zero as N increases towards infinity. If we instead exceed the limit, then as N increases, the communication will always fail (with probability approaching 1). So it is really becoming binary. Below the limit: Success. Above the limit: failure.
B is the bandwidth in Hz, but due to the sampling theorem it also equals the number of complex symbols per second. (The sampling theorem says that a signal with bandwidth B is uniquely described by 2B real samples per second or B complex samples.
This is a brief overview of the concept. If you want a more in-depth description, we recommend the following video: ruclips.net/video/VUZSf2NlTyM/видео.html In fact, there is an entire lecture series: ruclips.net/p/PLTv48TzNRhaJ66mW48MI_HBBawupV_ZR_
![Capacity of Point-to-point SIMO and MISO Channels [Video 5]](http://i.ytimg.com/vi/WJ1e_0sIJRk/mqdefault.jpg)
![Capacity of Point-to-point SIMO and MISO Channels [Video 5]](/img/tr.png)
![Signal-to-Noise Ratio in Wireless Communications [Video 1]](http://i.ytimg.com/vi/OA4viERrlzA/mqdefault.jpg)
Hello Thankyou for the detailed explaination - I have one question
If I have a Wi-Fi setup which provides me the following information at the receiver side -
RSSI (signal strength at the receiver) and the Noise floor in dB and the channel frequency response
is there any way i can evaluate the capacity of the channel with the above values as I have no acess to baseband signal to get the energy of each bits.?
The easiest thing would be to compute the SNR as the RSSI divided by the Noise power (be careful with the dB-scales). You can then estimate the capacity as "Bandwidth*log2(1+SNR)".
@@WirelessFuture Thankyou for the explaination , just a follow up question : Considering a 2x2 MIMO channel ,
I have the channel state information of received signal and RSSI and Noise Floor values of each Tx-Rx path, which formulae can I used to estimate the capacity of Wi-fi system ? considering rest other OFDM parameters (MCS, Bandwidth...etc ) is known to me. It would be reallly help- ful for my Thesis work. Thankyou in advance :)
sir your lectures are very much useful.
Dear Mr. Bjornson,
You have an incredible way to convey your knowledge :)
Could you plz make for us a video to explain why the data rate is related to the frequency bandwidth using Fourier transform ?
Thx a lot
You don’t need to involve the Fourier transform. Just apply the sampling theorem, which says that a signal is described by a number of samples proportional to the bandwidth. These samples are used to carry information, for example, by designing the signals using pulse-amplitude modulation. It is briefly mentioned in Video 3 and around slide 22 in ruclips.net/video/SR10FeiuAFs/видео.html
@@WirelessFuture thx a lot
00:48 is possible to have a non-symmetric two-sided spectrum??
Yes, but then the time-domain signal will be complex valued, so such a signal doesn’t exist in practice. However, the non-symmetric complex baseband signal exist and is usually represented as two different signals. (The “in-phase” and “quadrature” signals)
@@WirelessFuture ... but the graph is representing a baseband 2-sided spectrum.... is that possible?
♥️😍
another piece of cake
but the equation @3:07 should not be in (Symbol/second) instead (bits/s) because i think it's going to be bits/s after modulating the symbols isn't it ?
If you pause the video at 2:34, you will see expressions in symbol/s and in bit/symbol. If we multiply them together it becomes bit/s. This what is presented at 3:07.
Thank you so much...very nice explanation.
The Shannon limit says there is an upper bound for a reliable communication. Then what is the meaning of "reliable communication"? In other words, if one exceeds the limit, how much deterioration will be brought about?
Suppose we transmit a block of N modulation symbols (samples). If their information content is below the Shannon limit, there is a way to encode the information (select the symbols) so that the probability of incorrect reception of the block goes to zero as N increases towards infinity. If we instead exceed the limit, then as N increases, the communication will always fail (with probability approaching 1). So it is really becoming binary. Below the limit: Success. Above the limit: failure.
@@WirelessFuture Thank you very much! Great explanation!
Thank you very much
B (Symbol/sec) and B (Bandwidth) , I have a confused in this abbreviations
B is the bandwidth in Hz, but due to the sampling theorem it also equals the number of complex symbols per second. (The sampling theorem says that a signal with bandwidth B is uniquely described by 2B real samples per second or B complex samples.
Nice video
how log2 (1+z)= log2(e)!!!
log2(1+z)≈log2(e)*z when z is close to zero.
@@WirelessFuture okai thank you
Very bad. You talk without thinking about us understanding. Your just reading of some text. Try to be better.
This is a brief overview of the concept. If you want a more in-depth description, we recommend the following video: ruclips.net/video/VUZSf2NlTyM/видео.html
In fact, there is an entire lecture series: ruclips.net/p/PLTv48TzNRhaJ66mW48MI_HBBawupV_ZR_